## Comments on the 8/26/13 version of the NPRM, provided by OMB and

representing interagency review

Monte Carlo Analysis

A. Please provide analytic justifications for using the Monte Carlo analysis approach using the distributions chosen. It strikes the reviewer that this approach doesn’t reduce the arbitrariness or the underlying uncertainties better than simply adding up the ranges while making the analytics more complicated than necessary.

B. In general, it seems Monte Carlo is the wrong approach for estimating volumes. It might

forecast a most likely volume, but there is asymmetric risk in this instance. If volumes are too low, no harm no foul. If volumes are too high, then the prices of RINs will be high and we will face a real problem.

C. Page 79. “...We then used a Monte Carlo process i n which each of the six distributions were randomly sampled in an iterative fashion. The results of all the iterations were then summed to produce a distribution...” The distributions you are drawing on are likely correlated (perhaps significantly?) are th ey not? Thus uncorrelated draws across the distributions may be misleading? We might expect correlation because of 1) Correlated response to oil/energy prices 2) Correlated crop yields within the US 3) Simply correlated based on RIN prices (higher RIN
pri ces would increase the availability) again endogenous to the rule making. Please discuss how

non

- independent distributions may affect your results and solicit comment on analyses that may provide additional sensitivity to those results.



### D. Monte Carlo approa ch

– general comments . The Monte Carlo (MC) approach to aggregating results from different distributions is methodologically sound because there

are not closed

- form analytic results for the distribution created as the sum of the random
variables with the assumed distributions. Additionally, the assumed families of distributions seem reasonable. The comment here concerns the implementation of the MC aggregation and reporting of results.

The basic concern is that the MC approach is used to set multiple ag gregates, and ranges are given for comment, however the only internally consistent aggregation method is the mean (means add, medians don’t) and the ranges proposed for comment are at different levels of aggregation. Addressing this seems important both b ecause comments are solicited on measures other than the mean, and because (as is discussed below) there is a compelling policy/economic reason to consider measures other than the mean, in particular for the estimate of total ethanol that can be reasonably consumed.

Before making a suggestion, it is useful to lay out the following categories, which are intended to be mutually exclusive and exhaustive:

Category Ethanol Non

- Ethanol Sum

A. Renewable Fuels

Cellulosic D3E D3N D3

Biodiesel (B100)

- D4N D4

### Advanced residual D5E D5N D5

Renewable residual D6E

- D6

B. End

- use fuels

E10 E10

- E

E15 E15

- E

E85 E85

- E

Here, D4N is the ethanol

- equivalent volume of B100, etc; E10

- E is the ethanol volume
contained in E10 that is consumed. This omits end

- use diesel for convenience because it
doesn’t enter into the MC calculations.

The following sums are important under option 3:

1. Consumable Ethanol = E10

- E + E15

- E + E85

- E

2. D3 = D3E + D3N

3. D4 = D4N

4. Advanced RVO = D3 + D4 + D5N

5. Total renewable = Consumable Ethanol + D3N + D4N + D5N

The following is an interesting number but not needed for the mandate

“corn + cane ethanol” = Consumable Ethanol

– D3E

As a technical matter, the problem is that the only measure of a distribution that satisfies the

addition co nstraints 1

- 5 is the mean. So although comments are solicited about using, say, medians or quartiles, if those were deemed preferred, the current methodology would not support their use. So the technical challenge is, how to present ranges for comment, b ut at the same time preserve the internal addition constraints. The difficulties this poses are most evident in the discussion surrounding Figure IV.D.1.

Here is a proposal for resolving the need for internal consistency while (a) providing ranges

for co mment and (b) making sure the aggregation doesn’t inadvertently cause problems for the key feature of the blendwall:

1. Report MC aggregation results at the level of the sub

- component cells for renewable fuels (D3E, D3N, D4N, D5E, D5N, D6E). Some of these ( e.g. D3N) require MC aggregation, whereas others are just posited distributions. Report Mean, Mode, 10%, 25%, 50%, 75%, 90%. (Some of these distributions are degenerate, for example E10

- E is a singleton based on EIA forecasts and E15

- E is zero.)

2. Propose using the mean for each of those cells, but solicit comments on other

measures of the distribution.

3. Based on this single number chosen for each cell (in the NPRM, the mean, but possibly based on comments another measure in the final rule), compute the su ms.

4. The cellulosic mandate is D3.

### 5. The biodiesel mandate is 1.28Bg, however the value for D4 (the mean of the D4N distribution) would be carried forward to compute the total renewable volume, so that

D4

- 1.28 would be available to meet the D5 or D6 manda te as is proposed.

6. The advanced mandate and the total renewable mandate are also the sum of individual numbers (means in the NPRM), not the mean of separate MCs.

A drawback of this approach is that it does not give ranges for, say, the total renewable mandate, however as a practical matter comments on that range would not be expected because by itself it has no direct implications.

For Consumable Ethanol, it would be appropriate to aggregate this by Monte Carlo and report a distribution for consumable renewables. The reason is that, as a policy/economic matter, the loss associated with the Consumable Ethanol is asymmetric (see comment bubble, p. 59). Thus there is an argument for using a quantile of the distribution other than the mean, for example th e 25 th 

### percentile if the loss of overestimation is three times the loss from underestimation. In terms of the internal consistency argument, hypothetically choosing the 25 th 

### percentile of this distribution would not be a problem in

terms of the calculatio ns because that value only shows up in sum 5 above, the sum for
total renewable.

Given the single numerical values for Cellulosic, Biodiesel, Advanced, and Total Renewable, which are all now internally consistent, it is possible to compute the
renewable s tandards as outlined in the NPRM.

Finally, there might be an argument to carry out the MC for D3 to the D3 level of aggregation, not just D3N and D3E, but the “neutral” terminology suggests that the mean would be used anyway so this shouldn’t matter much (so OK either way).

A s a minor methodological comment we would suggest using many more draws, say 50,000, to reflect current professional practice. Also, EPA might consider using the summary table above (the D3N, etc table) as a guide to the calculations

.

Fu el and RIN Markets

E. What is the target RIN price?

F. What is EPA’s expected RI N price if the numbers in the proposal were the same in the final?

G. There needs to be a buffer volume so that the market has some margin in which to operate without sending prices high.

H. We are concerned that lack of a buffer and lack of market transparency also creates an opportunity for market manipulation.

I. The estimates of E85 volumes are too high and not substantiated. Similar concerns about the

estimates of biodiesel.J. Page 43. “... We also see no need to increase it. We believe that volumes of biomass

- based

diesel above 1.28 billion gallons can, and likely will, be produced in 2014 to meet the requirements of the advanced biofuel standard ...” Without the $1.00 per gallon blenders credit this seems a rather strong statement given the proposed level for the other mandates classes and limited need to consume additional undefined advanced, and the resulting volumes we might expect to see competition between E85 and bio

- based d iesel beyond its own mandate. Some support to the conclusion of ‘excess’ biodiesel consumption may clarify this statement.

K. Page 55. “... For purposes of determining the total renewable fuel volume requirement for 2014,

consistent with the waiver authoriti es we are proposing to exercise in this action, we have assessed the volume of E85 that can reasonably be supplied to and consumed by consumers, based on a variety of factors that limit supplying E85 in the transportation sector ...” “Reasonably” here direct ly relates to RIN prices and the volume of E85 used is not exogenous to this rule making. We can reasonably expect that this rule will push down RIN prices (perhaps significantly) which will also reduce the motivation to consume additional E85 volumes. In subsequent periods this establishes a certain amount of ‘path dependency’ limiting expansion of ethanol use in higher level blends. While not mandating this level, the rule has the effect of ‘centering’ use on this volume and setting a lower E85 and E15 expansion path into the future.

L. Page 55. “... The low consumption is most likely due primarily to limited access to retail stations offering E85 and the fact that the price of E85 was only about 13% lower than the price of E10 in

2013..” Is this not avera ges weighted by station and not by volume? If so this is a distorted look at E85 pricing. Recent station by station volume and price data out of Minnesota would show that volume weighted sales prices have moved much closer to ‘mileage equivalence’ while al so showing significant volume response to this pricing.

M. Page 58. “... The price relationship between E85 and E10 is primarily dependent on the prices of corn and crude oil, and is reflected in the price of RINs ...” This is true at the wholesale level based on the blending components when comparing E85 and E10. When comparing the price relationship between E10 and E85 at the retail level under a binding mandate, the RIN price is endogenous to this relationship.N. Page 58. “... Due to the paucity of data correlating E85 sales with its price relative to E10, we

have turned to other sources to help inform our projections...” See the graphs on MN above for examples of demand response to relative E85 pricing.

O. Page 58. DOE’s a nalysis of the max sales potential was very limited. Ask for comment on this. Suggested change: “... Based on assumptions about E85 tank sizes at retail stations and the associated refill frequencies, DOE estimated that the maximum sales of E85 would be 60 0 mill gal. However, this volume assumes that the number of retail stations offering E85 is about
2,300. We estimate that the number of stations offering E85 will be closer to 3,300 in 2014, which would correspond to a maximum E85 throughput of about 860 mill gal. That analysis did not consider alternative refill frequencies or refill volumes and so we ask for comment and data that would help refine our estimates of the potential maximum sales volumes of E85 for 2014...”

P. Page 59. EPA should acknowledge th e impact of lowering the standards will have on RIN prices and how that could affect sales of higher blends. Suggested change: “...Therefore we believe that 400 mill gal is a reasonable upper end of the range of possible volumes of E85 for 2014. We

acknowl edge that the price of E85 will also be a function of RIN prices. To the extent that the proposed volumes lead to lower RIN prices, the incentives for fuel vendors to market E85 and

other blends of ethanol above E10 will also be lower. We do not know the extent to which lower RIN prices will result in diminished incentives for those higher blends, but request comment and data from the public that would help estimate the impact of lowering volumetric requirements on the incentive to sell higher ethanol ble nds than E10...”

Q. Page 68. Combining tables IV.B 4

- 1, Table IV.C.1.a

- 1 and Table I

- 1. You can calculate the potential market for ethanol imports at approximately 158 million gallons (see below). This is less than has been imported this year to date into the US (through June 2013).

R. Page 76. “...The historical volumes of sugarcane ethanol imports into the U.S. from Brazil are indicative of Brazilian production and export capacity, and thus provide several benchmarks for the volume that could potentially be imported into the U.S. in 2014 ...” Many of the reports inTable IV.C.1.d

- 1 show import volumes that are heavily influenced by the mandate levels

considered. Most of these studies come to these import needs by the level of mandates set, that is to say the export volume doesn’t set the ma ndate rather the reverse occurs in these dynamic modeling system. Those are the import levels needed to help meet the undefined advanced gap in the most cost effective manner, not an exogenous trade level that is taken as ‘potential supplies’ into the US m arket. Price, heavily influenced by RIN prices (both import ethanol price and D5 RIN prices) are important considerations in how much supply will come into the US. This

makes the last line of Table IV.C.1.e

- 1 hard to interpret. Please provide accompanying discussion to that point.



### S. Biodiesel costs . Here are the comments on biodiesel costs referred to in the comment bubble on pp. 42

- 43.
There are several difficulties with the discussion of the effect of the biodiesel RFS mandate

on costs.

First, the fact that prices went up during the drought, and down after wards , neither proves nor disproves anything about the price impact of the RFS on soybeans. It simply proves that there is more than one factor that affects soybean prices, in this case rainfall is such an

additional factor.

Second, as long as there is a nonzero long

- run price elasticity, the RFS will have an impact on prices. When the RFS is binding, it moves out the demand curve which moves along the supply curve and prices go up. I t will be binding whenever the cost of using biofuels exceeds the cost of B0 or, equivalently, whenever the RIN price is positive. The long

- run elasticity is

nonzero because of limited land. This price effect will be there even with technological

progres s/improved productivity because demand is higher with the RFS than without. This logic should be stated squarely. If one wants to estimate cost impacts on soy prices, then USDA can provide estimates of soy oil supply elasticities and that should give a

s traightforward estimate of the price effects of the RFS on soy oil (or alternatively this could be taken back to the level of soybeans). There is a recent metastudy by NCEE (Condon, Klemik, and Wolverton, NCEE WP 2013

- 05) that discusses many estimates of the effect of the RFS on corn prices, perhaps there are some references there that might be useful for the

biodiesel issue here.

Third, Glauber’s testimony focused on U.S. food prices. Yes, the biodiesel component of the

RFS will have a small effect on o verall food prices, but this is because soy oil is a very small

fraction of the end

- product food price index in the U.S. Whether the RFS has a small impact on food prices isn’t the right metric

– in theory it could have a large impact on soy prices (and t hus affect consumers of soy products) but still have a very small effect on an overall

end

- consumption food price index.

Fourth, the previous comment raises the question of what is a large cost and what is a small cost. Total dollar impact is one way to approach this but CEA would argue that a better way to approach this question is to estimate costs of the biodiesel program in terms of dollars per
ton of CO2 emissions reduction. Such a metric addresses several of the bullet criteria listed on pp. 40

- 41. The economically “correct” way to do this calculation is to estimate the consumer and producer surplus forgone under the mandate as the cost, and to calculate the

### CO2 emissions reduction obtained, and compute from this a cost per ton. However, a back

of

- the

- envelope calculation can be done to give an order of magnitude.

This back

- of

- the

- envelope calculation is done in the table below. This calculation asks, (a) what is the direct dollar cost (not producer/consumer surplus, just dollar cost) of using a gallon of B100, in excess of using a gallon of B0, and (b) what is the GHG emissions reduction from using that gallon, and (c) dividing (a) by (b) gives an estimate of the cost per ton. This calculation is done below and yields an estimate of $314/ton. Note that this estimate is an underestimate because it excludes the losses suffered by consumers of food soy. It also depends on the price of soy diesel. Also, this calculation is a total cost, because it

does not net out the biodiesel tax credit. If th e biodiesel tax credit is taken as given, the marginal cost of the RFS would be less. But, consistent with the NPRM, if one assumes that the biodiesel tax credit will not be present for 2014, then this represents a full cost.

Cost/Metric Ton of Substit uting Biodiesel for Petroleum Diesel

Day used for blended biodiesel fuel and biodiesel RIN prices 8/8/2013
Mandate year 2013

Price of petroleum diesel (B0) ($/gal) $ 3.040 Price of biodiesel (B100) ($/gal) $ 4.730

Price of biodiesel RIN ($/gal) $ 1.118

Biodiesel share of mandate 0.011 Price of blended biodiesel fuel ($/gal) $ 3.793
Carbon emissions of petroleum diesel (B0) (kg/gal) 14.200 Carbon emissions of biodiesel (B100) (kg/gal) 5.623

Biodiesel tax credit $ 1.00
Difference in carbon emissions between petroleum diesel and biodiesel (kg/gal) 8.577 Cost of substituting biodiesel for petroleum diesel ($/kg) $ 0.3136
Cost of substituting biodiesel for petroleum diesel ($/metric ton) $ 314

Sources: Bloomberg, Environmental Protection Agency, Biomass Energy Centre

Note: This calculation assumes perfectly competitive markets in the biodiesel
producer and diesel blender markets, meaning that all subsidies are passed
directly to the consumer.

The price of B100 is taken from a "Fuel Pricing in 2013.docx" document sent from
the National Biodiesel Board. The price quoted is the price that producers sell for

a gallon of biodiesel. It appears that the price already includes the effect of the
tax credit. The price of B0 is taken to be the price of home heating oil.

The calculated price of blended biodiesel fuel includes a mark

- up of $0.74.



### The cost of approximately $300/ton is large compared with the updated SCC (which, for 2013 emissions in 2013 dollars with a 3% discount rate, is $43/ton. Viewed this way, the cost of using a marginal gallon of biodiesel is significant.

T. Forward guidance

.

### o As EPA k nows, because of the forward

- looking nature of RINs and of biofuels investments, it is key that the market have clear forward guidance. The rule uses different language on this point, in some places saying that the proposed 2014 methodology “could also be applied” in later years, in other places, in other places saying “we would intend this framework to apply not just to 2014, but to later years as well” (p.13), and other wording is used to. To avoid confusion, it would be helpful to go through the docume nt to align wording throughout with the stronger p. 13 wording.

o The methodology raises the question of how EPA might handle the part of the statute requiring resetting the RVOs for 2016 and beyond, subject to the
20%/two

- year trigger. It seems very likel y that EPA will confront this at some point as it moves along this path. It would seem appropriate to recognize this in the preamble and to indicate that the restatement is intended to be addressed within the context of the methodology and supply consider ations laid out in the 2014 rule. Some more careful wording than the previous sentence might be in order, but again the goal is to provide the market with forward guidance.

Jet Fuel


### U. The NPRM states that “[t]he third approach that we evaluated, and the one that we are proposing today, includes both a consideration of the capability of the relevant industries to make qualifying renewable fuels available, either through domestic production or importation, and also the capability of the relevant industries to ensure that those renewable fuels are used as transportation fuel, heating oil, or jet fuel” (page 13). Does the NPRM affect/impact jet fuel? If so, does section 42 U.S.C. § 7571 et seq . apply? Additionally, the statement also appears to contradict the statement in the Summary paragraph that states that “[t]oday’s action ... would apply to all motor vehicle gasoline and diesel produced and imported in the year 2014” (page 1).

Benefit/Cost Analysis of Options

V. The agency doesn’t provide any benefit/cost analysis to ascertain which option maximizes social net benefits. Please provide the analysis.

Health Aspects

W. On Page 40 and 41: Are human health outcomes associated with a statutory reduction in the volume of renewable biofuel for 2014 and 2015 (which may be manifested through changes in water quality, air quality, and climate change) considered? These health outcomes may be associated with the reduction of particulate matter, carbon monoxide, and total hydrocarbons

found with the use of biofuels rath er than petroleum.

Editorial/Clarifications

X. Page 42 (second paragraph, 4 th line). significntly

– > significantly

Y. Page 43. “... WASDE’s June Outlook Report estimates that for the 2013/2014 marketing year (which includes the months of October through December 2013) soybean prices will range from$9.75

– $11.75 per bushel...” The SOYBEAN marketing year runs from September

– August , the

SOYBEAN OIL marketing year runs from October

- September. This section might take some clarification as soybeans still have 50%+ of their value in the meal and presumably you are concerned with the oil price share.